Set up libraries and directories

Read in data by run

Customize here as required per cellranger output naming convention * Note that "_" is reserved in Seurat (used as delimiter between an object key and a feature name) + https://github.com/satijalab/seurat/issues/3219

## 10X data contains more than one type and is being returned as a list containing matrices of each type.
## [1] "Column order consistent - antibody and gene expression"
## [1] "***********************************************"
## [1] "CellRanger Output dmso: 33538 features in 2478 cells"
## [1] "Feature counts range 0 to 1643905"
## [1] "Features with 0 counts: 13356"
## [1] "Features with 1-3 counts: 3794"
## [1] "Cell feature counts range 500 to 107283"
## [1] "Cells with 500 counts: 1"
## [1] "CellRanger Antibody Output dmso: 8 features in 2478 cells"
## [1] "Antibody counts range 53493 to 712715"
## [1] "Antibody with 53493 counts: 1"
## [1] "Cell antibody counts range 34 to 367054"
## [1] "Cells with 34 counts: 1"
## [1] "dmso: 0 cells in ADT matrix that are not present in gene expression matrix"
## [1] "dmso: 0 cells in gene expression matrix that are not present in ADT matrix"
## 10X data contains more than one type and is being returned as a list containing matrices of each type.
## [1] "Column order consistent - antibody and gene expression"
## [1] "***********************************************"
## [1] "CellRanger Output ava: 33538 features in 4029 cells"
## [1] "Feature counts range 0 to 2103100"
## [1] "Features with 0 counts: 12871"
## [1] "Features with 1-3 counts: 3755"
## [1] "Cell feature counts range 500 to 80112"
## [1] "Cells with 500 counts: 5"
## [1] "CellRanger Antibody Output ava: 8 features in 4029 cells"
## [1] "Antibody counts range 65529 to 776274"
## [1] "Antibody with 65529 counts: 1"
## [1] "Cell antibody counts range 5 to 251337"
## [1] "Cells with 5 counts: 1"
## [1] "ava: 0 cells in ADT matrix that are not present in gene expression matrix"
## [1] "ava: 0 cells in gene expression matrix that are not present in ADT matrix"
## 10X data contains more than one type and is being returned as a list containing matrices of each type.
## [1] "Column order consistent - antibody and gene expression"
## [1] "***********************************************"
## [1] "CellRanger Output ory: 33538 features in 4212 cells"
## [1] "Feature counts range 0 to 2516846"
## [1] "Features with 0 counts: 12744"
## [1] "Features with 1-3 counts: 3692"
## [1] "Cell feature counts range 501 to 62086"
## [1] "Cells with 501 counts: 2"
## [1] "CellRanger Antibody Output ory: 8 features in 4212 cells"
## [1] "Antibody counts range 140493 to 715041"
## [1] "Antibody with 140493 counts: 1"
## [1] "Cell antibody counts range 1 to 160862"
## [1] "Cells with 1 counts: 1"
## [1] "ory: 0 cells in ADT matrix that are not present in gene expression matrix"
## [1] "ory: 0 cells in gene expression matrix that are not present in ADT matrix"
## 10X data contains more than one type and is being returned as a list containing matrices of each type.
## [1] "Column order consistent - antibody and gene expression"
## [1] "***********************************************"
## [1] "CellRanger Output combo: 33538 features in 2349 cells"
## [1] "Feature counts range 0 to 1401365"
## [1] "Features with 0 counts: 13633"
## [1] "Features with 1-3 counts: 3719"
## [1] "Cell feature counts range 502 to 66262"
## [1] "Cells with 502 counts: 1"
## [1] "CellRanger Antibody Output combo: 8 features in 2349 cells"
## [1] "Antibody counts range 129232 to 509767"
## [1] "Antibody with 129232 counts: 1"
## [1] "Cell antibody counts range 11 to 172768"
## [1] "Cells with 11 counts: 1"
## [1] "combo: 0 cells in ADT matrix that are not present in gene expression matrix"
## [1] "combo: 0 cells in gene expression matrix that are not present in ADT matrix"

Take a quick look at ADT concordance

## [1] "ab-CD10:  MME RNA present in fewer than 3 cells in dmso object"
## [1] "ab-CD90:  THY1 RNA present in fewer than 3 cells in dmso object"

## Warning in xy.coords(x, y, xlabel, ylabel, log): 1 y value <= 0 omitted from
## logarithmic plot

## Warning in xy.coords(x, y, xlabel, ylabel, log): 1 y value <= 0 omitted from
## logarithmic plot

## [1] "ab-CD10:  MME RNA present in fewer than 3 cells in ava object"
## [1] "ab-CD90:  THY1 RNA present in fewer than 3 cells in ava object"
## Warning in xy.coords(x, y, xlabel, ylabel, log): 8 y values <= 0 omitted from
## logarithmic plot

## Warning in xy.coords(x, y, xlabel, ylabel, log): 1 y value <= 0 omitted from
## logarithmic plot

## Warning in xy.coords(x, y, xlabel, ylabel, log): 1 y value <= 0 omitted from
## logarithmic plot

## Warning in xy.coords(x, y, xlabel, ylabel, log): 1 y value <= 0 omitted from
## logarithmic plot

## Warning in xy.coords(x, y, xlabel, ylabel, log): 2 y values <= 0 omitted from
## logarithmic plot

## [1] "ab-CD10:  MME RNA present in fewer than 3 cells in ory object"
## [1] "ab-CD90:  THY1 RNA present in fewer than 3 cells in ory object"
## Warning in xy.coords(x, y, xlabel, ylabel, log): 2 y values <= 0 omitted from
## logarithmic plot

## Warning in xy.coords(x, y, xlabel, ylabel, log): 1 y value <= 0 omitted from
## logarithmic plot

## Warning in xy.coords(x, y, xlabel, ylabel, log): 1 y value <= 0 omitted from
## logarithmic plot

## Warning in xy.coords(x, y, xlabel, ylabel, log): 1 y value <= 0 omitted from
## logarithmic plot

## Warning in xy.coords(x, y, xlabel, ylabel, log): 3 y values <= 0 omitted from
## logarithmic plot

## [1] "ab-CD10:  MME RNA present in fewer than 3 cells in combo object"
## [1] "ab-CD90:  THY1 RNA present in fewer than 3 cells in combo object"
## Warning in xy.coords(x, y, xlabel, ylabel, log): 11 y values <= 0 omitted from
## logarithmic plot

## Warning in xy.coords(x, y, xlabel, ylabel, log): 1 y value <= 0 omitted from
## logarithmic plot

## Warning in xy.coords(x, y, xlabel, ylabel, log): 7 y values <= 0 omitted from
## logarithmic plot

Summary Plots

Summarize data to make filtering decisions

Preprocess Runs

Based on summary plots, filter out cells with excess mitochondrial RNA, low/high counts Assign Cell Cycle Scores

## [1] "dmso:  Filter cells > 12% mitochondria: 563/2341 (24.0%)"
## [1] "dmso:  Filter cells with 200 > nCount > 25000: 122/2341 (5.2%)"
## [1] "Filtered dmso:  1657 cells, 16953 features"
## Warning: The following features are not present in the object: PIMREG, not
## searching for symbol synonyms
## [1] "ava:  Filter cells > 12% mitochondria: 996/3829 (26.0%)"
## [1] "ava:  Filter cells with 200 > nCount > 25000: 79/3829 (2.1%)"
## [1] "Filtered ava:  2754 cells, 17515 features"
## [1] "ory:  Filter cells > 12% mitochondria: 542/4070 (13.3%)"
## [1] "ory:  Filter cells with 200 > nCount > 25000: 124/4070 (3.0%)"
## [1] "Filtered ory:  3404 cells, 17700 features"
## [1] "combo:  Filter cells > 12% mitochondria: 263/2292 (11.5%)"
## [1] "combo:  Filter cells with 200 > nCount > 25000: 156/2292 (6.8%)"
## [1] "Filtered combo:  1873 cells, 16787 features"
## Warning: The following features are not present in the object: RAD51, not
## searching for symbol synonyms

Normalize & Scale

Quick look to assess regression needs

## Centering and scaling data matrix
## PC_ 1 
## Positive:  FCER1G, CYBB, CD14, NCF2, SLC7A11, CTSB, C5AR1, CTSL, NRP1, MAFB 
##     EMP1, CLEC5A, S100A9, CCR1, DUSP6, CD300E, FTL, ANXA5, NPC2, PLAUR 
##     CD93, ATP13A3, SIRPA, ITGAX, RBM47, TIMP1, SLC16A3, RAB31, CSF1R, CXCL8 
## Negative:  RPS18, ITM2A, GBP4, EGFL7, SEPT6, SOX4, STMN1, CXCR4, GBP2, GYPC 
##     LYSMD2, NCOA7, SERPINB1, FAM117A, SLC27A2, RHEX, HMGN3, SPN, ARHGEF6, PDCD4 
##     PTMA, SMYD3, MYB, APEX1, ERG, IRF1, MIS18BP1, DDB2, ABCC4, ANGPT1 
## PC_ 2 
## Positive:  SERPINB1, HLA-DRA, GSN, CELF2, H2AFY, HLA-DRB1, DBI, LGALS1, CD74, HLA-DRB5 
##     TFPI, ITM2A, GOLIM4, EGFL7, SEPT11, SLC27A2, SPN, NEAT1, HLA-DMA, TXN 
##     ARHGEF6, CD9, GBP4, SOX4, VMP1, CDK6, ETS2, PYGL, NCOA7, ORAI2 
## Negative:  CD3G, CD3E, CD2, CD3D, TRBC1, SYNE2, CCL5, CD81, SAMD3, CD247 
##     GIMAP4, LCK, SPOCK2, RORA, FYN, GZMH, NKG7, TRAC, GZMB, LSP1 
##     BTG1, GZMM, IKZF3, C12orf75, LINC01871, GIMAP7, CLEC2D, CLIC3, KLRD1, CD8A 
## PC_ 3 
## Positive:  NCF1, ADAM28, CFP, GPR183, DAPP1, FCGR2B, MARCKSL1, ALOX5, CSF2RA, FAM129A 
##     GLIPR1, PSTPIP2, LST1, RASA4, CEBPD, ITGB2, PPA1, HLA-DQB1, LYZ, CLEC10A 
##     NAV1, MARCH1, AC064805.1, SLC38A1, YWHAH, HLA-DRB1, PALLD, PTGIR, IGSF6, PKIB 
## Negative:  GCSAML, SLC27A2, CXCL5, CPA3, GATA2, CD163, CYTOR, MSR1, RHEX, MT2A 
##     RAB33A, CXCL3, CXCL1, NPL, HS3ST1, RNASE1, IKZF2, IQGAP2, FAM117A, CXCL2 
##     ANGPT1, PLIN2, SPTBN1, FAM171A1, NTRK1, ZFP36L1, CTSL, HACD1, MERTK, ZBTB16 
## PC_ 4 
## Positive:  CD79A, IGHM, MS4A1, PLCG2, CD79B, TNFRSF13C, BANK1, RALGPS2, LINC02397, IGHD 
##     TCL1A, IGKC, AFF3, VPREB3, PLEKHG1, POU2AF1, SPIB, C16orf74, LTB, LINC00926 
##     RAB30, CCR7, FAM30A, IGLC3, AC025164.1, BLNK, IGLC2, BASP1, FAM177B, SESN3 
## Negative:  CCL5, CST7, NKG7, IL32, GZMH, SAMD3, RARRES3, CD3G, TMSB4X, GZMB 
##     OASL, CD2, CD3D, LY6E, SLFN5, CD3E, ISG15, C12orf75, ANXA1, C1orf21 
##     GNLY, SH2D2A, KLRD1, STAT1, KLRG1, CXCR3, GZMM, CD8B, SPN, LINC01871 
## PC_ 5 
## Positive:  PYCARD, LAT2, CLEC11A, LST1, NME1, TPSAB1, DDX21, GAPT, LMO4, EIF4EBP1 
##     AL034397.3, ALOX5AP, PRSS57, NFE2, S100A8, GMPR, LYZ, CEBPA, S100A4, CPA3 
##     MYC, RNASE2, ITGB2, RAB37, CSTA, IGSF6, CD300LF, XBP1, CST3, GDF11 
## Negative:  CCR7, TNFSF4, NRP2, PALLD, CYTIP, PDE4B, TSC22D1, CD83, NEAT1, DUSP5 
##     DAPP1, MS4A7, CXCR4, C1QTNF1, MTSS1, ADA, CDKN1A, TNFRSF4, BHLHE41, FAM107B 
##     KLF6, AR, ARMC9, IL10RA, KYNU, SIPA1L1, ITGB8, SSH1, ISG20, EBI3
## Regressing out percent.mt
## Centering and scaling data matrix
## PC_ 1 
## Positive:  FCER1G, CYBB, CD14, NCF2, SLC7A11, CTSB, C5AR1, NRP1, CTSL, MAFB 
##     CLEC5A, EMP1, S100A9, CCR1, DUSP6, CD300E, FTL, ANXA5, NPC2, PLAUR 
##     CD93, ATP13A3, SIRPA, ITGAX, TIMP1, RBM47, SLC16A3, CSF1R, RAB31, CXCL8 
## Negative:  RPS18, ITM2A, GBP4, EGFL7, SEPT6, SOX4, STMN1, CXCR4, GBP2, GYPC 
##     LYSMD2, NCOA7, SERPINB1, SLC27A2, FAM117A, SPN, RHEX, ARHGEF6, HMGN3, PDCD4 
##     SMYD3, PTMA, MYB, APEX1, ERG, IRF1, MIS18BP1, DDB2, ABCC4, ANGPT1 
## PC_ 2 
## Positive:  SERPINB1, HLA-DRA, CELF2, H2AFY, LGALS1, GSN, HLA-DRB1, DBI, TFPI, ITM2A 
##     HLA-DRB5, CD74, EGFL7, GOLIM4, TXN, SLC27A2, SEPT11, HLA-DMA, PKM, SOX4 
##     ARHGEF6, GBP4, CDK6, SPN, PYGL, RHEX, ETS2, NCOA7, SSBP2, FSCN1 
## Negative:  CD3G, CD3E, CD2, CD3D, TRBC1, CCL5, SYNE2, CD81, SAMD3, CD247 
##     LCK, GIMAP4, SPOCK2, RORA, GZMH, GZMB, GZMM, NKG7, FYN, TRAC 
##     LSP1, C12orf75, IKZF3, BTG1, LINC01871, CLIC3, KLRD1, GIMAP7, CD8A, CLEC2D 
## PC_ 3 
## Positive:  NCF1, ADAM28, CFP, GPR183, DAPP1, FCGR2B, MARCKSL1, CSF2RA, FAM129A, ALOX5 
##     GLIPR1, PSTPIP2, LST1, RASA4, CEBPD, HLA-DQB1, ITGB2, PPA1, LYZ, NAV1 
##     CLEC10A, MARCH1, HLA-DRB1, SLC38A1, AC064805.1, YWHAH, PTGIR, PALLD, IGSF6, HLA-DQA1 
## Negative:  GCSAML, SLC27A2, CPA3, GATA2, CXCL5, CYTOR, CD163, RHEX, MSR1, RAB33A 
##     MT2A, CXCL3, CXCL1, NPL, IKZF2, IQGAP2, FAM117A, ANGPT1, HS3ST1, CXCL2 
##     SPTBN1, RNASE1, PLIN2, FAM171A1, NTRK1, HACD1, CTSL, ZFP36L1, MERTK, ZBTB16 
## PC_ 4 
## Positive:  CD79A, IGHM, MS4A1, PLCG2, CD79B, TNFRSF13C, BANK1, RALGPS2, LINC02397, IGHD 
##     IGKC, TCL1A, CCR7, AFF3, VPREB3, SPIB, PLEKHG1, POU2AF1, LTB, C16orf74 
##     RAB30, LINC00926, CD83, IGLC3, BASP1, AC025164.1, FAM30A, SESN3, BLNK, IGLC2 
## Negative:  TMSB4X, NKG7, CCL5, CST7, RARRES3, GZMH, SAMD3, IL32, CD3G, GZMB 
##     OASL, CD3D, ISG15, CD2, LY6E, SPN, C12orf75, STAT1, SLFN5, CD3E 
##     DBI, ANXA1, C1orf21, SH2D2A, GNLY, SRGN, KLRD1, IQGAP2, IFI6, KLRG1 
## PC_ 5 
## Positive:  NRP2, TNFSF4, PALLD, CCR7, PDE4B, CYTIP, MS4A7, CXCR4, NEAT1, ADA 
##     TNFRSF4, TSC22D1, CDKN1A, DUSP5, DAPP1, MTSS1, C1QTNF1, KLF6, FAM107B, CD83 
##     AR, BHLHE41, EBI3, SSH1, ARMC9, SIPA1L1, PEAK1, ISG20, RFTN1, IL10RA 
## Negative:  PYCARD, LAT2, TPSAB1, LST1, GAPT, CLEC11A, NME1, S100A8, NFE2, AL034397.3 
##     LMO4, DDX21, LYZ, PRSS57, ALOX5AP, EIF4EBP1, GMPR, RNASE2, MYC, CEBPA 
##     S100A9, EGR1, CPA3, CD300LF, RAB37, CSTA, ITGB2, AC020656.1, IGSF6, CCNA1

## Regressing out Phase
## Centering and scaling data matrix
## PC_ 1 
## Positive:  FCER1G, CYBB, CD14, NCF2, SLC7A11, C5AR1, CTSB, CTSL, MAFB, NRP1 
##     EMP1, CLEC5A, CCR1, S100A9, CD300E, DUSP6, CD93, FTL, NPC2, ANXA5 
##     PLAUR, ATP13A3, ITGAX, SIRPA, RBM47, RAB31, SLC16A3, TIMP1, CXCL8, TGFBI 
## Negative:  RPS18, ITM2A, GBP4, SEPT6, EGFL7, SOX4, GBP2, STMN1, CXCR4, NCOA7 
##     LYSMD2, GYPC, SERPINB1, SLC27A2, FAM117A, SPN, HMGN3, ARHGEF6, RHEX, SMYD3 
##     PDCD4, MYB, PTMA, ERG, APEX1, DDB2, IRF1, ABCC4, MIS18BP1, ANGPT1 
## PC_ 2 
## Positive:  SERPINB1, HLA-DRA, GSN, CELF2, H2AFY, LGALS1, HLA-DRB1, DBI, CD74, HLA-DRB5 
##     ITM2A, EGFL7, TFPI, GOLIM4, SEPT11, NEAT1, SOX4, SLC27A2, SPN, TXN 
##     VMP1, ARHGEF6, HLA-DMA, PYGL, CD9, ETS2, RHEX, GBP4, CDK6, PKM 
## Negative:  CD3G, CD3E, CD2, CD3D, TRBC1, SYNE2, CCL5, CD81, SAMD3, CD247 
##     GIMAP4, LCK, SPOCK2, RORA, FYN, NKG7, GZMH, GZMB, TRAC, IKZF3 
##     LSP1, GZMM, BTG1, C12orf75, CLEC2D, GIMAP7, LINC01871, CLIC3, KLRD1, CD8A 
## PC_ 3 
## Positive:  NCF1, ADAM28, CFP, GPR183, FCGR2B, DAPP1, MARCKSL1, CSF2RA, ALOX5, PSTPIP2 
##     LST1, GLIPR1, FAM129A, RASA4, ITGB2, CEBPD, LYZ, PPA1, HLA-DQB1, CLEC10A 
##     MARCH1, NAV1, IGSF6, AC064805.1, YWHAH, HLA-DRB1, SLC38A1, TYMP, PTGIR, PALLD 
## Negative:  GCSAML, SLC27A2, CD163, CXCL5, GATA2, CPA3, CYTOR, MSR1, RHEX, CXCL3 
##     RAB33A, MT2A, CXCL1, NPL, CXCL2, HS3ST1, RNASE1, IKZF2, FAM117A, ANGPT1 
##     IQGAP2, SPTBN1, CTSL, ZFP36L1, PLIN2, FAM171A1, NTRK1, MERTK, HACD1, PPBP 
## PC_ 4 
## Positive:  CD79A, IGHM, PLCG2, MS4A1, CD79B, TNFRSF13C, BANK1, RALGPS2, LINC02397, IGHD 
##     IGKC, TCL1A, AFF3, VPREB3, SPIB, PLEKHG1, POU2AF1, CCR7, LTB, C16orf74 
##     RAB30, LINC00926, IGLC3, FAM30A, AC025164.1, CD83, BASP1, IGLC2, FAM177B, SESN3 
## Negative:  CCL5, NKG7, TMSB4X, CST7, RARRES3, IL32, GZMH, SAMD3, CD3G, CD3D 
##     OASL, GZMB, CD2, LY6E, ISG15, CD3E, C12orf75, SLFN5, STAT1, C1orf21 
##     ANXA1, GNLY, SPN, KLRD1, SH2D2A, KLRG1, IFI6, GZMM, CXCR3, CD8B 
## PC_ 5 
## Positive:  TNFSF4, NRP2, PALLD, CCR7, MS4A7, PDE4B, NEAT1, TSC22D1, ADA, DUSP5 
##     C1QTNF1, DAPP1, MTSS1, BHLHE41, CYTIP, KLF6, CXCR4, CDKN1A, CD83, TNFRSF4 
##     AR, ITGB8, ARMC9, FAM107B, IL10RA, SSH1, KYNU, ISG20, EBI3, FAM49A 
## Negative:  PYCARD, LAT2, NME1, LST1, DDX21, TPSAB1, CLEC11A, LMO4, EIF4EBP1, S100A8 
##     GAPT, ALOX5AP, CPA3, LYZ, NFE2, GMPR, PRSS57, S100A4, CSTA, GCSAML 
##     AL034397.3, CEBPA, IGSF6, S100A9, GDF11, CCNA1, ITGB2, EGR1, MYC, RNASE2

## Regressing out Phase, percent.mt
## Centering and scaling data matrix
## PC_ 1 
## Positive:  FCER1G, CYBB, CD14, NCF2, SLC7A11, CTSB, C5AR1, CTSL, NRP1, MAFB 
##     CLEC5A, EMP1, CCR1, S100A9, DUSP6, CD300E, CD93, FTL, NPC2, ANXA5 
##     PLAUR, ATP13A3, SIRPA, ITGAX, RBM47, RAB31, TIMP1, SLC16A3, CSF1R, TGFBI 
## Negative:  RPS18, ITM2A, GBP4, SEPT6, EGFL7, SOX4, GBP2, STMN1, CXCR4, NCOA7 
##     LYSMD2, GYPC, SERPINB1, SLC27A2, FAM117A, SPN, HMGN3, ARHGEF6, RHEX, PDCD4 
##     SMYD3, MYB, PTMA, ERG, APEX1, DDB2, IRF1, ABCC4, MIS18BP1, ANGPT1 
## PC_ 2 
## Positive:  SERPINB1, HLA-DRA, CELF2, H2AFY, LGALS1, GSN, HLA-DRB1, DBI, ITM2A, EGFL7 
##     TFPI, HLA-DRB5, TXN, GOLIM4, CD74, SOX4, SLC27A2, PKM, ARHGEF6, SEPT11 
##     HLA-DMA, RHEX, CDK6, GBP4, SPN, PYGL, ETS2, MYB, ERG, VMP1 
## Negative:  CD3G, CD3E, CD2, CD3D, TRBC1, CCL5, SYNE2, CD81, SAMD3, CD247 
##     LCK, GIMAP4, SPOCK2, RORA, GZMB, GZMH, NKG7, FYN, GZMM, TRAC 
##     LSP1, IKZF3, C12orf75, BTG1, LINC01871, CLIC3, KLRD1, CD8A, CLEC2D, GIMAP7 
## PC_ 3 
## Positive:  NCF1, ADAM28, CFP, GPR183, DAPP1, FCGR2B, MARCKSL1, CSF2RA, ALOX5, FAM129A 
##     GLIPR1, PSTPIP2, LST1, RASA4, ITGB2, CEBPD, LYZ, HLA-DQB1, PPA1, CLEC10A 
##     NAV1, MARCH1, HLA-DRB1, AC064805.1, IGSF6, YWHAH, SLC38A1, PTGIR, PALLD, TYMP 
## Negative:  GCSAML, SLC27A2, CPA3, GATA2, CD163, CYTOR, CXCL5, MSR1, RHEX, CXCL3 
##     RAB33A, MT2A, CXCL1, NPL, IKZF2, FAM117A, CXCL2, IQGAP2, ANGPT1, HS3ST1 
##     RNASE1, SPTBN1, FAM171A1, CTSL, PLIN2, ZFP36L1, NTRK1, HACD1, MERTK, ZBTB16 
## PC_ 4 
## Positive:  CD79A, IGHM, PLCG2, MS4A1, CD79B, TNFRSF13C, BANK1, RALGPS2, IGKC, LINC02397 
##     IGHD, TCL1A, CCR7, AFF3, VPREB3, SPIB, PLEKHG1, POU2AF1, LTB, CD83 
##     C16orf74, RAB30, LINC00926, BASP1, IGLC3, AC025164.1, SESN3, FAM30A, IGLC2, KYNU 
## Negative:  TMSB4X, NKG7, CCL5, RARRES3, CST7, GZMH, SAMD3, CD3D, CD3G, IL32 
##     OASL, GZMB, ISG15, SPN, LY6E, CD2, STAT1, C12orf75, DBI, CD3E 
##     SLFN5, C1orf21, ANXA1, SRGN, IQGAP2, GNLY, SH2D2A, PYCARD, IFI6, KLRD1 
## PC_ 5 
## Positive:  PALLD, NRP2, TNFSF4, ADA, MS4A7, PDE4B, MTSS1, NEAT1, CCR7, BHLHE41 
##     KLF6, DUSP5, C1QTNF1, TSC22D1, TNFRSF4, DAPP1, CXCR4, CDKN1A, CYTIP, AR 
##     EBI3, SSH1, FAM107B, RFTN1, ITGB8, CD83, ARMC9, ISG20, IL10RA, SIPA1L1 
## Negative:  PYCARD, LAT2, LST1, NME1, TPSAB1, S100A8, DDX21, GAPT, CPA3, LYZ 
##     EIF4EBP1, LMO4, ALOX5AP, CLEC11A, NFE2, EGR1, S100A9, CSTA, AL034397.3, GMPR 
##     PRSS57, RNASE2, MYC, CEBPA, CCNA1, ITGB2, GCSAML, CD300LF, IGSF6, RAB37

## Regressing out CC.Difference
## Centering and scaling data matrix
## PC_ 1 
## Positive:  FCER1G, CYBB, CD14, NCF2, SLC7A11, CTSB, C5AR1, CTSL, MAFB, NRP1 
##     EMP1, S100A9, CLEC5A, CCR1, CD300E, DUSP6, ANXA5, FTL, NPC2, CD93 
##     PLAUR, ATP13A3, SIRPA, ITGAX, RBM47, SLC16A3, TIMP1, RAB31, CXCL8, CSF1R 
## Negative:  RPS18, ITM2A, GBP4, EGFL7, SEPT6, SOX4, STMN1, GYPC, CXCR4, GBP2 
##     SERPINB1, LYSMD2, NCOA7, SLC27A2, FAM117A, ARHGEF6, SPN, HMGN3, RHEX, SMYD3 
##     PTMA, PDCD4, APEX1, MYB, ERG, IRF1, DDB2, ABCC4, MIS18BP1, ANGPT1 
## PC_ 2 
## Positive:  SERPINB1, HLA-DRA, GSN, CELF2, H2AFY, LGALS1, HLA-DRB1, DBI, TFPI, CD74 
##     ITM2A, HLA-DRB5, EGFL7, GOLIM4, SEPT11, NEAT1, SPN, VMP1, TXN, SLC27A2 
##     CD9, SOX4, ETS2, GBP4, HLA-DMA, ARHGEF6, PYGL, RHEX, NCOA7, CDK6 
## Negative:  CD3G, CD3E, CD2, CD3D, TRBC1, SYNE2, CCL5, CD81, SAMD3, CD247 
##     GIMAP4, LCK, SPOCK2, RORA, FYN, GZMH, TRAC, NKG7, GZMB, LSP1 
##     IKZF3, GZMM, BTG1, C12orf75, LINC01871, CLEC2D, GIMAP7, CLIC3, KLRD1, CD8A 
## PC_ 3 
## Positive:  NCF1, ADAM28, CFP, GPR183, DAPP1, FCGR2B, MARCKSL1, CSF2RA, ALOX5, PSTPIP2 
##     FAM129A, GLIPR1, LST1, RASA4, CEBPD, ITGB2, PPA1, LYZ, HLA-DQB1, CLEC10A 
##     NAV1, MARCH1, AC064805.1, YWHAH, SLC38A1, HLA-DRB1, IGSF6, PALLD, PTGIR, PKIB 
## Negative:  GCSAML, SLC27A2, CXCL5, CD163, GATA2, CPA3, CYTOR, MSR1, RHEX, CXCL3 
##     CXCL1, RAB33A, MT2A, NPL, HS3ST1, CXCL2, RNASE1, FAM117A, IKZF2, IQGAP2 
##     ANGPT1, PLIN2, SPTBN1, FAM171A1, CTSL, NTRK1, ZFP36L1, MERTK, HACD1, PPBP 
## PC_ 4 
## Positive:  CD79A, PLCG2, IGHM, MS4A1, CD79B, TNFRSF13C, BANK1, RALGPS2, LINC02397, IGHD 
##     TCL1A, IGKC, AFF3, VPREB3, CCR7, SPIB, PLEKHG1, POU2AF1, LTB, C16orf74 
##     RAB30, LINC00926, IGLC3, FAM30A, AC025164.1, CD83, BASP1, SESN3, IGLC2, FAM177B 
## Negative:  CCL5, NKG7, CST7, TMSB4X, RARRES3, SAMD3, GZMH, CD3G, IL32, CD3D 
##     GZMB, CD2, OASL, C12orf75, CD3E, LY6E, ISG15, SLFN5, C1orf21, SH2D2A 
##     GNLY, STAT1, KLRD1, SPN, KLRG1, CD8B, IFI6, GZMM, CXCR3, TRBC1 
## PC_ 5 
## Positive:  TNFSF4, PALLD, NRP2, NEAT1, PDE4B, MS4A7, CYTIP, CCR7, TSC22D1, ADA 
##     CXCR4, MTSS1, DUSP5, C1QTNF1, KLF6, BHLHE41, DAPP1, CDKN1A, TNFRSF4, AR 
##     FAM107B, IL10RA, SSH1, KYNU, ARMC9, EBI3, CD83, ISG20, ITGB8, RFTN1 
## Negative:  PYCARD, NME1, LAT2, DDX21, LST1, TPSAB1, EIF4EBP1, CLEC11A, MYC, LMO4 
##     HSPE1, NFE2, PRSS57, GAPT, S100A8, CSTA, GMPR, LYZ, ALOX5AP, CEBPA 
##     CPA3, AL034397.3, RNASE2, RPL22L1, XBP1, CCNA1, EGR1, MRPL12, CD300LF, RAB37

## Regressing out CC.Difference, percent.mt
## Centering and scaling data matrix
## PC_ 1 
## Positive:  FCER1G, CYBB, CD14, NCF2, SLC7A11, CTSB, C5AR1, NRP1, CTSL, MAFB 
##     CLEC5A, EMP1, S100A9, CCR1, CD300E, DUSP6, ANXA5, FTL, NPC2, PLAUR 
##     CD93, ATP13A3, SIRPA, ITGAX, RBM47, SLC16A3, TIMP1, CSF1R, RAB31, CXCL8 
## Negative:  RPS18, ITM2A, GBP4, EGFL7, SEPT6, SOX4, STMN1, GYPC, CXCR4, GBP2 
##     SERPINB1, LYSMD2, NCOA7, SLC27A2, FAM117A, SPN, ARHGEF6, HMGN3, RHEX, SMYD3 
##     PTMA, PDCD4, APEX1, MYB, ERG, IRF1, DDB2, ABCC4, MIS18BP1, ANGPT1 
## PC_ 2 
## Positive:  SERPINB1, HLA-DRA, CELF2, H2AFY, LGALS1, GSN, HLA-DRB1, DBI, ITM2A, TFPI 
##     EGFL7, TXN, HLA-DRB5, GOLIM4, CD74, PKM, SOX4, SLC27A2, SEPT11, HLA-DMA 
##     RHEX, GBP4, ARHGEF6, ETS2, PYGL, SPN, CDK6, VMP1, FSCN1, ERG 
## Negative:  CD3G, CD3E, CD2, CD3D, TRBC1, SYNE2, CCL5, CD81, SAMD3, CD247 
##     LCK, GIMAP4, SPOCK2, RORA, GZMH, GZMB, FYN, GZMM, NKG7, TRAC 
##     LSP1, C12orf75, IKZF3, LINC01871, CLIC3, BTG1, KLRD1, CLEC2D, GIMAP7, CD8A 
## PC_ 3 
## Positive:  NCF1, ADAM28, CFP, GPR183, DAPP1, FCGR2B, MARCKSL1, CSF2RA, FAM129A, ALOX5 
##     GLIPR1, PSTPIP2, LST1, RASA4, CEBPD, ITGB2, HLA-DQB1, PPA1, LYZ, NAV1 
##     CLEC10A, MARCH1, HLA-DRB1, SLC38A1, YWHAH, AC064805.1, PTGIR, PALLD, IGSF6, HLA-DQA1 
## Negative:  GCSAML, SLC27A2, CPA3, GATA2, CXCL5, CD163, CYTOR, RHEX, MSR1, RAB33A 
##     CXCL3, MT2A, CXCL1, NPL, IKZF2, FAM117A, IQGAP2, ANGPT1, HS3ST1, CXCL2 
##     RNASE1, PLIN2, SPTBN1, FAM171A1, CTSL, NTRK1, HACD1, ZFP36L1, MERTK, ZBTB16 
## PC_ 4 
## Positive:  CD79A, IGHM, PLCG2, MS4A1, CD79B, TNFRSF13C, BANK1, RALGPS2, IGKC, CCR7 
##     LINC02397, IGHD, TCL1A, AFF3, VPREB3, SPIB, PLEKHG1, POU2AF1, LTB, CD83 
##     C16orf74, RAB30, LINC00926, KYNU, TSC22D1, BASP1, SAT1, AC025164.1, IGLC3, NEAT1 
## Negative:  TMSB4X, NKG7, CCL5, CST7, RARRES3, GZMH, SAMD3, CD3D, CD3G, GZMB 
##     CD2, IL32, OASL, ISG15, LY6E, C12orf75, SPN, CD3E, ASPM, STAT1 
##     SRM, DBI, SH2D2A, SLFN5, C1orf21, GNLY, PYCARD, IFI6, IQGAP2, ITGA4 
## PC_ 5 
## Positive:  PYCARD, LAT2, NME1, DDX21, LST1, TPSAB1, EIF4EBP1, MYC, CLEC11A, GAPT 
##     NFE2, S100A8, LYZ, LMO4, PRSS57, AL034397.3, EGR1, CEBPA, HSPE1, RNASE2 
##     GMPR, CPA3, ALOX5AP, CSTA, S100A9, CCNA1, CD300LF, ASNS, RAB37, XBP1 
## Negative:  PALLD, TNFSF4, NRP2, MS4A7, PDE4B, ADA, NEAT1, MTSS1, CYTIP, CXCR4 
##     TNFRSF4, CDKN1A, KLF6, TSC22D1, DUSP5, C1QTNF1, BHLHE41, DAPP1, AR, CCR7 
##     FAM107B, SSH1, EBI3, PTMS, IL10RA, RFTN1, PEAK1, F2RL3, ARMC9, SIPA1L1

Assign Cell-Cycle Scores

So - filter first, then assign cell cycle scores

## Picking joint bandwidth of 0.362
## Picking joint bandwidth of 0.113
## Picking joint bandwidth of 0.775
## Picking joint bandwidth of 0.506

## [1] "Sum the counts in s-phase genes across 1657 cells"
##    CLSPN     NASP     USP1      DTL     EXO1     RRM2     MSH2   POLR1B 
##       75     2198      815       19        5       14      244      162 
##     MCM6    CDCA7     SLBP    CENPU   MRPL36     GMNN CASP8AP2     RFC2 
##      178      126     1207      109      948      283      556      387 
##     MCM7    POLA1     MCM4    CCNE2    DSCC1    ATAD2     RRM1     E2F8 
##      413      147      140      239       24      321      363        9 
##     FEN1    POLD3    HELLS RAD51AP1    PRIM1      UNG     UBR7    RAD51 
##      139      492      214       55      113       76      212        2 
##    WDR76    TIPIN      BLM    GINS2     CDC6     TYMS     PCNA    UHRF1 
##      120      173      233       32       22      142      471       50 
##    CDC45     MCM5   CHAF1B 
##        6      440       11 
## [1] "Sum the counts in g2m-phase genes across 1657 cells"
##   CDCA8   CDC20   KIF2C   PSRC1  ANP32E   CKS1B    NUF2    NEK2   CENPF     LBR 
##      42      32      25       5    1319     319      30      10     193    2278 
##   CENPA    BUB1  CKAP2L   HJURP    SMC4    ECT2   TACC3   CENPE   HMGB2  CDC25C 
##       8      53      28      17    1360     139     588      54    2070       7 
##    HMMR     TTK    ANLN   CDCA2    CKS2  TUBB4B   CKAP5    CDK1  KIF20B   KIF11 
##      55      16      26      21     465    5430     647      28     367      61 
##   MKI67  NCAPD2   CDCA3    CBX5    TMPO  GAS2L3   CKAP2    G2E3  DLGAP5  NUSAP1 
##      51     320      14     841    1860     173     635     618      25     149 
##   CCNB2   KIF23    CTCF   AURKB   TOP2A    JPT1   BIRC5   NDC80    TPX2   UBE2C 
##      69     130    1446      19     171    3870      24      36      92      38 
##   AURKA RANGAP1   GTSE1 
##     201     337      32
## Picking joint bandwidth of 0.316
## Picking joint bandwidth of 0.194
## Picking joint bandwidth of 0.931
## Picking joint bandwidth of 0.539

## [1] "Sum the counts in s-phase genes across 2754 cells"
##    CLSPN     NASP     USP1      DTL     EXO1     RRM2     MSH2   POLR1B 
##      116     3152     1279       58       12       26      353      224 
##     MCM6    CDCA7     SLBP    CENPU   MRPL36     GMNN CASP8AP2     RFC2 
##      264      179     1713      191     1269      414      770      478 
##     MCM7    POLA1     MCM4    CCNE2    DSCC1    ATAD2     RRM1     E2F8 
##      593      195      260      343       40      445      537        6 
##     FEN1    POLD3    HELLS RAD51AP1    PRIM1      UNG     UBR7    RAD51 
##      210      746      276       91      156      105      317        3 
##    WDR76    TIPIN      BLM    GINS2     CDC6     TYMS     PCNA    UHRF1 
##      175      268      312       86       29      208      634       75 
##    CDC45     MCM5   CHAF1B 
##       20      691       23 
## [1] "Sum the counts in g2m-phase genes across 2754 cells"
##   CDCA8   CDC20   KIF2C   PSRC1  ANP32E   CKS1B    NUF2    NEK2   CENPF     LBR 
##      65      61      44      14    1925     492      61      23     437    3344 
##   CENPA    BUB1  CKAP2L   HJURP    SMC4    ECT2   TACC3   CENPE   HMGB2  CDC25C 
##      16      92      43      45    1960     209     811     130    3123      11 
##    HMMR     TTK    ANLN   CDCA2    CKS2  TUBB4B   CKAP5    CDK1  KIF20B   KIF11 
##     108      39      38      13     617    7680     962      92     627     116 
##   MKI67  NCAPD2   CDCA3    CBX5    TMPO  GAS2L3   CKAP2    G2E3  DLGAP5  NUSAP1 
##     147     516      15    1286    2626     242     914     905      55     338 
##   CCNB2   KIF23    CTCF  PIMREG   AURKB   TOP2A    JPT1   BIRC5   NDC80    TPX2 
##     105     187    2253       5      39     369    5714     107      74     167 
##   UBE2C   AURKA RANGAP1   GTSE1 
##     100     360     451      69
## Picking joint bandwidth of 0.355
## Picking joint bandwidth of 0.177
## Picking joint bandwidth of 0.761
## Picking joint bandwidth of 0.618

## [1] "Sum the counts in s-phase genes across 3404 cells"
##    CLSPN     NASP     USP1      DTL     EXO1     RRM2     MSH2   POLR1B 
##      152     3912     1398       52       13       44      365      313 
##     MCM6    CDCA7     SLBP    CENPU   MRPL36     GMNN CASP8AP2     RFC2 
##      352      221     2112      208     1839      483      922      640 
##     MCM7    POLA1     MCM4    CCNE2    DSCC1    ATAD2     RRM1     E2F8 
##      737      244      245      510       39      628      563       16 
##     FEN1    POLD3    HELLS RAD51AP1    PRIM1      UNG     UBR7    RAD51 
##      226     1052      388      137      186      139      389        3 
##    WDR76    TIPIN      BLM    GINS2     CDC6     TYMS     PCNA    UHRF1 
##      218      345      370       87       47      335      779       88 
##    CDC45     MCM5   CHAF1B 
##       23      780       31 
## [1] "Sum the counts in g2m-phase genes across 3404 cells"
##   CDCA8   CDC20   KIF2C   PSRC1  ANP32E   CKS1B    NUF2    NEK2   CENPF     LBR 
##      87      74      56      19    2417     629      74      21     478    4118 
##   CENPA    BUB1  CKAP2L   HJURP    SMC4    ECT2   TACC3   CENPE   HMGB2  CDC25C 
##      31      77      70      54    2264     279    1029     121    4535      14 
##    HMMR     TTK    ANLN   CDCA2    CKS2  TUBB4B   CKAP5    CDK1  KIF20B   KIF11 
##     120      34      52      30     865   10706    1139     109     705     157 
##   MKI67  NCAPD2   CDCA3    CBX5    TMPO  GAS2L3   CKAP2    G2E3  DLGAP5  NUSAP1 
##     192     604      28    1572    3671     267    1019    1112      64     376 
##   CCNB2   KIF23    CTCF  PIMREG   AURKB   TOP2A    JPT1   BIRC5   NDC80    TPX2 
##     140     293    2525       5      49     437    7593     126      92     190 
##   UBE2C   AURKA RANGAP1   GTSE1 
##     151     391     606      80
## Picking joint bandwidth of 0.255
## Picking joint bandwidth of 0.118
## Picking joint bandwidth of 0.644
## Picking joint bandwidth of 0.334

## [1] "Sum the counts in s-phase genes across 1873 cells"
##    CLSPN     NASP     USP1      DTL     EXO1     RRM2     MSH2   POLR1B 
##       77     2022      917       28        7       14      161      136 
##     MCM6    CDCA7     SLBP    CENPU   MRPL36     GMNN CASP8AP2     RFC2 
##      170      106     1167       78      879      238      599      350 
##     MCM7    POLA1     MCM4    CCNE2    DSCC1    ATAD2     RRM1     E2F8 
##      394      133      139      233       19      390      318        9 
##     FEN1    POLD3    HELLS RAD51AP1    PRIM1      UNG     UBR7    WDR76 
##      130      547      255       62       76       55      210      102 
##    TIPIN      BLM    GINS2     CDC6     TYMS     PCNA    UHRF1    CDC45 
##      152      200       20       23      130      451       56       10 
##     MCM5   CHAF1B 
##      451       20 
## [1] "Sum the counts in g2m-phase genes across 1873 cells"
##   CDCA8   CDC20   KIF2C   PSRC1  ANP32E   CKS1B    NUF2    NEK2   CENPF     LBR 
##      44      38      22      10    1058     251      30       9     235    2312 
##   CENPA    BUB1  CKAP2L   HJURP    SMC4    ECT2   TACC3   CENPE   HMGB2  CDC25C 
##      18      36      25      15    1575     135     592      92    2018       2 
##    HMMR     TTK    ANLN   CDCA2    CKS2  TUBB4B   CKAP5    CDK1  KIF20B   KIF11 
##      44      16      26      14     331    5679     629      34     420      75 
##   MKI67  NCAPD2   CDCA3    CBX5    TMPO  GAS2L3   CKAP2    G2E3  DLGAP5  NUSAP1 
##     133     343      13     854    1850     175     492     530      21     196 
##   CCNB2   KIF23    CTCF  PIMREG   AURKB   TOP2A    JPT1   BIRC5   NDC80    TPX2 
##      64     123    1564       3      21     219    3512      53      39     102 
##   UBE2C   AURKA RANGAP1   GTSE1 
##      56     214     328      44

Save Data

If you add filtering, make sure that you adjust the file saving accordingly

## [1] "Saving preprocessed data in individual objects in aml_eto.preprocSO.nofilt.2021-01-05.rds"
## R version 4.0.2 (2020-06-22)
## Platform: x86_64-apple-darwin17.0 (64-bit)
## Running under: macOS Catalina 10.15.7
## 
## Matrix products: default
## BLAS:   /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRblas.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRlapack.dylib
## 
## locale:
## [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
## 
## attached base packages:
## [1] stats     graphics  grDevices utils     datasets  methods   base     
## 
## other attached packages:
## [1] dplyr_1.0.2       patchwork_1.0.1   networkD3_0.4     knitr_1.30       
## [5] ggplot2_3.3.2     data.table_1.13.0 Seurat_3.2.2     
## 
## loaded via a namespace (and not attached):
##  [1] nlme_3.1-149          matrixStats_0.57.0    RcppAnnoy_0.0.16     
##  [4] RColorBrewer_1.1-2    httr_1.4.2            sctransform_0.3      
##  [7] tools_4.0.2           R6_2.4.1              irlba_2.3.3          
## [10] rpart_4.1-15          KernSmooth_2.23-17    uwot_0.1.8           
## [13] mgcv_1.8-33           lazyeval_0.2.2        colorspace_1.4-1     
## [16] withr_2.3.0           tidyselect_1.1.0      gridExtra_2.3        
## [19] compiler_4.0.2        plotly_4.9.2.1        labeling_0.3         
## [22] scales_1.1.1          lmtest_0.9-38         spatstat.data_1.4-3  
## [25] ggridges_0.5.2        pbapply_1.4-3         spatstat_1.64-1      
## [28] goftest_1.2-2         stringr_1.4.0         digest_0.6.25        
## [31] spatstat.utils_1.17-0 rmarkdown_2.4         pkgconfig_2.0.3      
## [34] htmltools_0.5.0       fastmap_1.0.1         htmlwidgets_1.5.2    
## [37] rlang_0.4.7           shiny_1.5.0           farver_2.0.3         
## [40] generics_0.0.2        zoo_1.8-8             jsonlite_1.7.1       
## [43] ica_1.0-2             magrittr_1.5          Matrix_1.2-18        
## [46] Rcpp_1.0.5            munsell_0.5.0         abind_1.4-5          
## [49] reticulate_1.16       lifecycle_0.2.0       stringi_1.5.3        
## [52] yaml_2.2.1            MASS_7.3-53           Rtsne_0.15           
## [55] plyr_1.8.6            grid_4.0.2            parallel_4.0.2       
## [58] listenv_0.8.0         promises_1.1.1        ggrepel_0.8.2        
## [61] crayon_1.3.4          deldir_0.1-29         miniUI_0.1.1.1       
## [64] lattice_0.20-41       cowplot_1.1.0         splines_4.0.2        
## [67] tensor_1.5            pillar_1.4.6          igraph_1.2.5         
## [70] future.apply_1.6.0    reshape2_1.4.4        codetools_0.2-16     
## [73] leiden_0.3.3          glue_1.4.2            evaluate_0.14        
## [76] vctrs_0.3.4           png_0.1-7             httpuv_1.5.4         
## [79] gtable_0.3.0          RANN_2.6.1            purrr_0.3.4          
## [82] polyclip_1.10-0       tidyr_1.1.2           future_1.19.1        
## [85] xfun_0.18             rsvd_1.0.3            mime_0.9             
## [88] xtable_1.8-4          later_1.1.0.1         survival_3.2-7       
## [91] viridisLite_0.3.0     tibble_3.0.3          cluster_2.1.0        
## [94] globals_0.13.0        fitdistrplus_1.1-1    ellipsis_0.3.1       
## [97] ROCR_1.0-11